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VulnerabilityPublished Updated

CVE-2026-27025: py-pdf pypdf · Excessive Iteration

Affects py-pdf pypdfSource CVE Database V5

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Not known to be exploited · CVSS 6.9 Medium : upgrade to 6.7.1 when convenient.

Data as of 29 Oct 2026, 19:04 UTC

CVSS 4.0 base score
6.9Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.1% chance of exploitation in 30 days – higher than 8% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 6.7.1
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 20 Feb 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

What to do

Upgrade py-pdf pypdf to 6.7.1.

Affected software

ProductAffectedFixed in
py-pdfpypdfAffected
  • <6.7.1
Fixed in
  • 6.7.1

AI-suggested

To mitigate CVE-2026-27025, organizations should upgrade all instances of the pypdf library to version 6.7.1 or later, where the vulnerability is fixed. For environments where immediate upgrade is not feasible, implementing input validation or sandboxing of PDF processing tasks can reduce risk. Limiting resource allocation (CPU and memory) for PDF parsing processes can help contain potential denial of service effects. Monitoring for unusually high resource consumption during PDF processing and alerting on anomalies can provide early detection. Additionally, restricting the acceptance of PDFs from untrusted or unauthenticated sources reduces exposure. Developers should review and harden any custom PDF parsing code to avoid excessive iteration patterns. Incorporating rate limiting or queuing mechanisms for PDF processing jobs can further mitigate impact. Finally, maintaining an inventory of software dependencies and applying timely security updates is critical to prevent exploitation.

Description

### Impact An attacker who uses this vulnerability can craft a PDF which leads to long runtimes and large memory consumption. This requires parsing the `/ToUnicode` entry of a font with unusually large values, for example during text extraction. ### Patches This has been fixed in [pypdf==6.7.1](https://github.com/py-pdf/pypdf/releases/tag/6.7.1). ### Workarounds If you cannot upgrade yet, consider applying the changes from PR [#3646](https://github.com/py-pdf/pypdf/pull/3646).

References

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